Boolean Network-Based Sensor Selection with Application to the Fault Diagnosis of a Nuclear Plant

Zhe Dong
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Zhe Dong: Institute of Nuclear and New Energy Technology, Collaborative Innovation Centre of Advanced Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China

Energies, 2017, vol. 10, issue 12, 1-13

Abstract: Fault diagnosis is crucial for the operation of energy systems such as nuclear plants, and heavily relies on various types of sensors for temperature, pressure, concentration, etc. Due to the redundancy of sensors in each energy system, the sensor selection scheme can deeply influence the diagnostic efficiency. In this paper, a Boolean network (BN) with its linear representation is proposed for describing the fault propagation among sensors. Both the sufficient condition of fault detectability and that of fault discriminability are given. Then, a sensor selection method for fault detection and discrimination is proposed. Finally, the theoretic result is applied to realize the diagnosis oriented sensor selection for a nuclear steam supply system based on a modular high temperature gas-cooled reactor (MHTGR). The computation and simulation results verify the correctness of the theoretical results.

Keywords: fault diagnosis; nuclear plant; sensor selection; semi-tensor product (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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